Predictive plasma biomarker for gestational diabetes: A case-control study in China

Area of Science:

• Biochemistry
• Reproductive Endocrinology
• Clinical Diagnostics

Background:

• Gestational diabetes mellitus (GDM) poses risks to maternal and fetal health.
• Early detection of GDM is crucial for timely intervention and management.
• Existing biomarkers for GDM lack sufficient sensitivity and specificity in early pregnancy.

Purpose of the Study:

• To identify novel plasma biomarkers for the early prediction and diagnosis of GDM.
• To evaluate the diagnostic accuracy of potential biomarkers in the first and second trimesters of pregnancy.
• To assess the combined predictive value of identified biomarkers with existing clinical indicators.

Main Methods:

• Proteomic analysis of placental tissues from women with GDM and normal glucose tolerance (NGT).
• Validation of differentially expressed proteins (DEPs) in maternal plasma using Luminex assays.
• Correlation analysis of biomarker levels with blood lipid indexes and logistic regression for predictive modeling.
• Receiver operating characteristic (ROC) curve analysis to determine diagnostic accuracy.

Main Results:

• 123 DEPs were identified in placental tissue, associated with key metabolic and inflammatory pathways.
• Plasma GAL-3BP levels were significantly elevated in women with GDM compared to NGT in both early and mid-pregnancy.
• A combined predictive model using triglycerides (TG) and GAL-3BP demonstrated a high diagnostic accuracy (AUC 0.69) for GDM in early pregnancy.

Conclusions:

• Plasma TG and GAL-3BP are valuable biomarkers for the early prediction and diagnosis of GDM.
• These biomarkers can help differentiate between women with GDM and NGT in early pregnancy.
• The findings support the potential clinical utility of TG and GAL-3BP for GDM screening.